On a defect identification method based on monitoring the structure and peculiarities of surface wave fields-Reference-Cited by-同舟云学术

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On a defect identification method based on monitoring the structure and peculiarities of surface wave fields

Published:2016-07 Issue:7 Volume:52 Page:377-382
ISSN:1061-8309
Container-title:Russian Journal of Nondestructive Testing
language:en
Short-container-title:Russ J Nondestruct Test

Author:

Bocharova O. V.,Sedov A. V.,Andzhikovich I. E.,Kalinchuk V. V.

Publisher

Pleiades Publishing Ltd

Subject

Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science

Link

http://link.springer.com/content/pdf/10.1134/S1061830916070020.pdf

Reference16 articles.

1. Dervilis, N., Choi, M., Barthorpe, R.J., Park, G., Farrar, C.R., and Worden, K., On damage diagnosis for a wind turbine blade using pattern recognition, J. Sound Vib., 2014, vol. 333, no. 6, pp. 1833–1850.

2. Salazar, A., Vargara, L., and Llinares, R., Learning material defect patterns by separating mixtures of independent component analyzers from NDT sonic signals, Mech. Syst. Signal Process., 2010, vol. 24, no. 6, pp. 1870–1886.

3. Tsui, P.C. and Basir, O.A., Wavelet basis selection and feature extraction for shift invariant ultrasound foreign body classification, Ultrasonics, 2006, vol. 45, nos. 1–4, pp. 1–14.

4. Tondreau, G. and Deraemaeker, A., Local modal filters for automated data-based damage localization using ambient vibrations, Mech. Syst. Signal Process, 2013, vol. 39, nos. 1–2, pp. 162–180.

5. Ismagilov, I.R., Golenishchev-Kutuzov, V.A., Kalimullin, R.I., Migachev, S.A., and Khasanov, A.A., Detecting surface and volume defects in metals by the laser-acoustic method, Russ. J. Nondestr. Test., 2014, vol. 50, no. 6, pp. 318–324.

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